This paper proposes a dynamic joint quantile regression model for estimating VaR and ES of multiple financial assets in one step, extending the univariate framework of [1]}.
To implement the methodology, we suggest a likelihood-based approach based on the MAL density proposed in [2]}, generalized to the case of time-varying parameters. This offers a powerful tool to model the dynamics of multiple VaR and ES jointly. blackIndeed, the location parameter of the MAL density represents the vector of VaRs, while the ES can be expressed as a simple function of the density scale parameter.
